Author(s):
Oliosi, Eduarda ; Júlio, Afonso Caetano ; Silva, Luís ; Probst, Phillip ; Vilas-Boas, João Paulo ; Pinheiro, Ana Rita ; Gamboa, Hugo
Date: 2025
Persistent ID: http://hdl.handle.net/10362/184530
Origin: Repositório Institucional da UNL
Project/scholarship:
info:eu-repo/grantAgreement/FCT/Concurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico em Ciência dos dados e inteligência artificial na Administração Pública - 2019/DSAIPA%2FAI%2F0105%2F2019/PT;
info:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F05913%2F2020/PT;
info:eu-repo/grantAgreement/FCT/OE/PRT%2FBD%2F152843%2F2021/PT;
Subject(s): Chronic pain; Inertial sensors; Musculoskeletal disorders; Pain intensity; Postural control; Variability; Analytical Chemistry; Information Systems; Atomic and Molecular Physics, and Optics; Biochemistry; Instrumentation; Electrical and Electronic Engineering
Description
Funding Information: This study was partially funded by the Portuguese Foundation for Science and Technology (FCT) through the project PREVOCUPAI (DSAIPA/AI/0105/2019). This work also received support provided by the FCT, I.P., and the European Union under the project UIDB/05913/2020—Centre for Research, Education, Innovation, and Intervention in Sport (https://doi.org/10.54499/UIDB/05913/2020). P. Probst was supported by the doctoral grant PRT/BD/152843/2021, financed by the FCT and with funds from the State Budget, under the MIT Portugal Program. Publisher Copyright: © 2025 by the authors.
This pilot study examines the relationship between pain intensity and trunk sitting postural control in 10 office workers with chronic spinal pain, using field-based real-time inertial sensors. Pain intensity was assessed with the Numeric Pain Rating Scale (NPRS) before and after work across three non-consecutive workdays, while postural control was evaluated through estimated center of pressure (COP) displacements. Linear and nonlinear metrics, including sway range, velocity, the Hurst exponent, and sample entropy, were derived from the estimated COP time series. Pearson correlation coefficients (r) and corresponding p-values were used to analyze the relationship between pain intensity and postural control. Significant correlations, though limited to specific metrics, were found (r = −0.860 to 0.855; p < 0.05), suggesting that higher pain intensity may be correlated with reduced postural variability. These findings provide preliminary insights into the potential link between pain intensity and postural control. Understanding trunk posture dynamics could inform the development of targeted ergonomic interventions to reduce musculoskeletal stress and improve sitting comfort in office environments.
